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#435619 Video Friday: Watch This Robot Dog ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
RoboBusiness 2019 – October 1-3, 2019 – Santa Clara, CA, USA
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

Team PLUTO (University of Pennsylvania, Ghost Robotics, and Exyn Technologies) put together this video giving us a robot’s-eye-view (or whatever they happen to be using for eyes) of the DARPA Subterranean Challenge tunnel circuits.

[ PLUTO ]

Zhifeng Huang has been improving his jet-stepping humanoid robot, which features new hardware and the ability to take larger and more complex steps.

This video reported the last progress of an ongoing project utilizing ducted-fan propulsion system to improve humanoid robot’s ability in stepping over large ditches. The landing point of the robot’s swing foot can be not only forward but also side direction. With keeping quasi-static balance, the robot was able to step over a ditch with 450mm in width (up to 97% of the robot’s leg’s length) in 3D stepping.

[ Paper ]

Thanks Zhifeng!

These underacuated hands from Matei Ciocarlie’s lab at Columbia are magically able to reconfigure themselves to grasp different object types with just one or two motors.

[ Paper ] via [ ROAM Lab ]

This is one reason we should pursue not “autonomous cars” but “fully autonomous cars” that never require humans to take over. We can’t be trusted.

During our early days as the Google self-driving car project, we invited some employees to test our vehicles on their commutes and weekend trips. What we were testing at the time was similar to the highway driver assist features that are now available on cars today, where the car takes over the boring parts of the driving, but if something outside its ability occurs, the driver has to take over immediately.

What we saw was that our testers put too much trust in that technology. They were doing things like texting, applying makeup, and even falling asleep that made it clear they would not be ready to take over driving if the vehicle asked them to. This is why we believe that nothing short of full autonomy will do.

[ Waymo ]

Buddy is a DIY and fetchingly minimalist social robot (of sorts) that will be coming to Kickstarter this month.

We have created a new arduino kit. His name is Buddy. He is a DIY social robot to serve as a replacement for Jibo, Cozmo, or any of the other bots that are no longer available. Fully 3D printed and supported he adds much more to our series of Arduino STEM robotics kits.

Buddy is able to look around and map his surroundings and react to changes within them. He can be surprised and he will always have a unique reaction to changes. The kit can be built very easily in less than an hour. It is even robust enough to take the abuse that kids can give it in a classroom.

[ Littlebots ]

The android Mindar, based on the Buddhist deity of mercy, preaches sermons at Kodaiji temple in Kyoto, and its human colleagues predict that with artificial intelligence it could one day acquire unlimited wisdom. Developed at a cost of almost $1 million (¥106 million) in a joint project between the Zen temple and robotics professor Hiroshi Ishiguro, the robot teaches about compassion and the dangers of desire, anger and ego.

[ Japan Times ]

I’m not sure whether it’s the sound or what, but this thing scares me for some reason.

[ BIRL ]

This gripper uses magnets as a sort of adjustable spring for dynamic stiffness control, which seems pretty clever.

[ Buffalo ]

What a package of medicine sees while being flown by drone from a hospital to a remote clinic in the Dominican Republic. The drone flew 11 km horizontally and 800 meters vertically, and I can’t even imagine what it would take to make that drive.

[ WeRobotics ]

My first ride in a fully autonomous car was at Stanford in 2009. I vividly remember getting in the back seat of a descendant of Junior, and watching the steering wheel turn by itself as the car executed a perfect parking maneuver. Ten years later, it’s still fun to watch other people have that experience.

[ Waymo ]

Flirtey, the pioneer of the commercial drone delivery industry, has unveiled the much-anticipated first video of its next-generation delivery drone, the Flirtey Eagle. The aircraft designer and manufacturer also unveiled the Flirtey Portal, a sophisticated take off and landing platform that enables scalable store-to-door operations; and an autonomous software platform that enables drones to deliver safely to homes.

[ Flirtey ]

EPFL scientists are developing new approaches for improved control of robotic hands – in particular for amputees – that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary proof-of-concept between neuroengineering and robotics was successfully tested on three amputees and seven healthy subjects.

[ EPFL ]

This video is a few years old, but we’ll take any excuse to watch the majestic sage-grouse be majestic in all their majesticness.

[ UC Davis ]

I like the idea of a game of soccer (or, football to you weirdos in the rest of the world) where the ball has a mind of its own.

[ Sphero ]

Looks like the whole delivery glider idea is really taking off! Or, you know, not taking off.

Weird that they didn’t show the landing, because it sure looked like it was going to plow into the side of the hill at full speed.

[ Yates ] via [ sUAS News ]

This video is from a 2018 paper, but it’s not like we ever get tired of seeing quadrupeds do stuff, right?

[ MIT ]

Founder and Head of Product, Ian Bernstein, and Head of Engineering, Morgan Bell, have been involved in the Misty project for years and they have learned a thing or two about building robots. Hear how and why Misty evolved into a robot development platform, learn what some of the earliest prototypes did (and why they didn’t work for what we envision), and take a deep dive into the technology decisions that form the Misty II platform.

[ Misty Robotics ]

Lex Fridman interviews Vijay Kumar on the Artifiical Intelligence Podcast.

[ AI Podcast ]

This week’s CMU RI Seminar is from Ross Knepper at Cornell, on Formalizing Teamwork in Human-Robot Interaction.

Robots out in the world today work for people but not with people. Before robots can work closely with ordinary people as part of a human-robot team in a home or office setting, robots need the ability to acquire a new mix of functional and social skills. Working with people requires a shared understanding of the task, capabilities, intentions, and background knowledge. For robots to act jointly as part of a team with people, they must engage in collaborative planning, which involves forming a consensus through an exchange of information about goals, capabilities, and partial plans. Often, much of this information is conveyed through implicit communication. In this talk, I formalize components of teamwork involving collaboration, communication, and representation. I illustrate how these concepts interact in the application of social navigation, which I argue is a first-class example of teamwork. In this setting, participants must avoid collision by legibly conveying intended passing sides via nonverbal cues like path shape. A topological representation using the braid groups enables the robot to reason about a small enumerable set of passing outcomes. I show how implicit communication of topological group plans achieves rapid covergence to a group consensus, and how a robot in the group can deliberately influence the ultimate outcome to maximize joint performance, yielding pedestrian comfort with the robot.

[ CMU RI ]

In this week’s episode of Robots in Depth, Per speaks with Julien Bourgeois about Claytronics, a project from Carnegie Mellon and Intel to develop “programmable matter.”

Julien started out as a computer scientist. He was always interested in robotics privately but then had the opportunity to get into micro robots when his lab was merged into the FEMTO-ST Institute. He later worked with Seth Copen Goldstein at Carnegie Mellon on the Claytronics project.

Julien shows an enlarged mock-up of the small robots that make up programmable matter, catoms, and speaks about how they are designed. Currently he is working on a unit that is one centimeter in diameter and he shows us the very small CPU that goes into that model.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435601 New Double 3 Robot Makes Telepresence ...

Today, Double Robotics is announcing Double 3, the latest major upgrade to its line of consumer(ish) telepresence robots. We had a (mostly) fantastic time testing out Double 2 back in 2016. One of the things that we found out back then was that it takes a lot of practice to remotely drive the robot around. Double 3 solves this problem by leveraging the substantial advances in 3D sensing and computing that have taken place over the past few years, giving their new robot a level of intelligence that promises to make telepresence more accessible for everyone.

Double 2’s iPad has been replaced by “a fully integrated solution”—which is a fancy way of saying a dedicated 9.7-inch touchscreen and a whole bunch of other stuff. That other stuff includes an NVIDIA Jetson TX2 AI computing module, a beamforming six-microphone array, an 8-watt speaker, a pair of 13-megapixel cameras (wide angle and zoom) on a tilting mount, five ultrasonic rangefinders, and most excitingly, a pair of Intel RealSense D430 depth sensors.

It’s those new depth sensors that really make Double 3 special. The D430 modules each uses a pair of stereo cameras with a pattern projector to generate 1280 x 720 depth data with a range of between 0.2 and 10 meters away. The Double 3 robot uses all of this high quality depth data to locate obstacles, but at this point, it still doesn’t drive completely autonomously. Instead, it presents the remote operator with a slick, augmented reality view of drivable areas in the form of a grid of dots. You just click where you want the robot to go, and it will skillfully take itself there while avoiding obstacles (including dynamic obstacles) and related mishaps along the way.

This effectively offloads the most stressful part of telepresence—not running into stuff—from the remote user to the robot itself, which is the way it should be. That makes it that much easier to encourage people to utilize telepresence for the first time. The way the system is implemented through augmented reality is particularly impressive, I think. It looks like it’s intuitive enough for an inexperienced user without being restrictive, and is a clever way of mitigating even significant amounts of lag.

Otherwise, Double 3’s mobility system is exactly the same as the one featured on Double 2. In fact, that you can stick a Double 3 head on a Double 2 body and it instantly becomes a Double 3. Double Robotics is thoughtfully offering this to current Double 2 owners as a significantly more affordable upgrade option than buying a whole new robot.

For more details on all of Double 3's new features, we spoke with the co-founders of Double Robotics, Marc DeVidts and David Cann.

IEEE Spectrum: Why use this augmented reality system instead of just letting the user click on a regular camera image? Why make things more visually complicated, especially for new users?

Marc DeVidts and David Cann: One of the things that we realized about nine months ago when we got this whole thing working was that without the mixed reality for driving, it was really too magical of an experience for the customer. Even us—we had a hard time understanding whether the robot could really see obstacles and understand where the floor is and that kind of thing. So, we said “What would be the best way of communicating this information to the user?” And the right way to do it ended up drawing the graphics directly onto the scene. It’s really awesome—we have a full, real time 3D scene with the depth information drawn on top of it. We’re starting with some relatively simple graphics, and we’ll be adding more graphics in the future to help the user understand what the robot is seeing.

How robust is the vision system when it comes to obstacle detection and avoidance? Does it work with featureless surfaces, IR absorbent surfaces, in low light, in direct sunlight, etc?

We’ve looked at all of those cases, and one of the reasons that we’re going with the RealSense is the projector that helps us to see blank walls. We also found that having two sensors—one facing the floor and one facing forward—gives us a great coverage area. Having ultrasonic sensors in there as well helps us to detect anything that we can't see with the cameras. They're sort of a last safety measure, especially useful for detecting glass.

It seems like there’s a lot more that you could do with this sensing and mapping capability. What else are you working on?

We're starting with this semi-autonomous driving variant, and we're doing a private beta of full mapping. So, we’re going to do full SLAM of your environment that will be mapped by multiple robots at the same time while you're driving, and then you'll be able to zoom out to a map and click anywhere and it will drive there. That's where we're going with it, but we want to take baby steps to get there. It's the obvious next step, I think, and there are a lot more possibilities there.

Do you expect developers to be excited for this new mapping capability?

We're using a very powerful computer in the robot, a NVIDIA Jetson TX2 running Ubuntu. There's room to grow. It’s actually really exciting to be able to see, in real time, the 3D pose of the robot along with all of the depth data that gets transformed in real time into one view that gives you a full map. Having all of that data and just putting those pieces together and getting everything to work has been a huge feat in of itself.

We have an extensive API for developers to do custom implementations, either for telepresence or other kinds of robotics research. Our system isn't running ROS, but we're going to be adding ROS adapters for all of our hardware components.

Telepresence robots depend heavily on wireless connectivity, which is usually not something that telepresence robotics companies like Double have direct control over. Have you found that connectivity has been getting significantly better since you first introduced Double?

When we started in 2013, we had a lot of customers that didn’t have WiFi in their hallways, just in the conference rooms. We very rarely hear about customers having WiFi connectivity issues these days. The bigger issue we see is when people are calling into the robot from home, where they don't have proper traffic management on their home network. The robot doesn't need a ton of bandwidth, but it does need consistent, low latency bandwidth. And so, if someone else in the house is watching Netflix or something like that, it’s going to saturate your connection. But for the most part, it’s gotten a lot better over the last few years, and it’s no longer a big problem for us.

Do you think 5G will make a significant difference to telepresence robots?

We’ll see. We like the low latency possibilities and the better bandwidth, but it's all going to be a matter of what kind of reception you get. LTE can be great, if you have good reception; it’s all about where the tower is. I’m pretty sure that WiFi is going to be the primary thing for at least the next few years.

DeVidts also mentioned that an unfortunate side effect of the new depth sensors is that hanging a t-shirt on your Double to give it some personality will likely render it partially blind, so that's just something to keep in mind. To make up for this, you can switch around the colorful trim surrounding the screen, which is nowhere near as fun.

When the Double 3 is ready for shipping in late September, US $2,000 will get you the new head with all the sensors and stuff, which seamlessly integrates with your Double 2 base. Buying Double 3 straight up (with the included charging dock) will run you $4,ooo. This is by no means an inexpensive robot, and my impression is that it’s not really designed for individual consumers. But for commercial, corporate, healthcare, or education applications, $4k for a robot as capable as the Double 3 is really quite a good deal—especially considering the kinds of use cases for which it’s ideal.

[ Double Robotics ] Continue reading

Posted in Human Robots

#435528 The Time for AI Is Now. Here’s Why

You hear a lot these days about the sheer transformative power of AI.

There’s pure intelligence: DeepMind’s algorithms readily beat humans at Go and StarCraft, and DeepStack triumphs over humans at no-limit hold’em poker. Often, these silicon brains generate gameplay strategies that don’t resemble anything from a human mind.

There’s astonishing speed: algorithms routinely surpass radiologists in diagnosing breast cancer, eye disease, and other ailments visible from medical imaging, essentially collapsing decades of expert training down to a few months.

Although AI’s silent touch is mainly felt today in the technological, financial, and health sectors, its impact across industries is rapidly spreading. At the Singularity University Global Summit in San Francisco this week Neil Jacobstein, Chair of AI and Robotics, painted a picture of a better AI-powered future for humanity that is already here.

Thanks to cloud-based cognitive platforms, sophisticated AI tools like deep learning are no longer relegated to academic labs. For startups looking to tackle humanity’s grand challenges, the tools to efficiently integrate AI into their missions are readily available. The progress of AI is massively accelerating—to the point you need help from AI to track its progress, joked Jacobstein.

Now is the time to consider how AI can impact your industry, and in the process, begin to envision a beneficial relationship with our machine coworkers. As Jacobstein stressed in his talk, the future of a brain-machine mindmeld is a collaborative intelligence that augments our own. “AI is reinventing the way we invent,” he said.

AI’s Rapid Revolution
Machine learning and other AI-based methods may seem academic and abstruse. But Jacobstein pointed out that there are already plenty of real-world AI application frameworks.

Their secret? Rather than coding from scratch, smaller companies—with big visions—are tapping into cloud-based solutions such as Google’s TensorFlow, Microsoft’s Azure, or Amazon’s AWS to kick off their AI journey. These platforms act as all-in-one solutions that not only clean and organize data, but also contain built-in security and drag-and-drop coding that allow anyone to experiment with complicated machine learning algorithms.

Google Cloud’s Anthos, for example, lets anyone migrate data from other servers—IBM Watson or AWS, for example—so users can leverage different computing platforms and algorithms to transform data into insights and solutions.

Rather than coding from scratch, it’s already possible to hop onto a platform and play around with it, said Jacobstein. That’s key: this democratization of AI is how anyone can begin exploring solutions to problems we didn’t even know we had, or those long thought improbable.

The acceleration is only continuing. Much of AI’s mind-bending pace is thanks to a massive infusion of funding. Microsoft recently injected $1 billion into OpenAI, the Elon Musk venture that engineers socially responsible artificial general intelligence (AGI).

The other revolution is in hardware, and Google, IBM, and NVIDIA—among others—are racing to manufacture computing chips tailored to machine learning.

Democratizing AI is like the birth of the printing press. Mechanical printing allowed anyone to become an author; today, an iPhone lets anyone film a movie masterpiece.

However, this diffusion of AI into the fabric of our lives means tech explorers need to bring skepticism to their AI solutions, giving them a dose of empathy, nuance, and humanity.

A Path Towards Ethical AI
The democratization of AI is a double-edged sword: as more people wield the technology’s power in real-world applications, problems embedded in deep learning threaten to disrupt those very judgment calls.

Much of the press on the dangers of AI focuses on superintelligence—AI that’s more adept at learning than humans—taking over the world, said Jacobstein. But the near-term threat, and far more insidious, is in humans misusing the technology.

Deepfakes, for example, allow AI rookies to paste one person’s head on a different body or put words into a person’s mouth. As the panel said, it pays to think of AI as a cybersecurity problem, one with currently shaky accountability and complexity, and one that fails at diversity and bias.

Take bias. Thanks to progress in natural language processing, Google Translate works nearly perfectly today, so much so that many consider the translation problem solved. Not true, the panel said. One famous example is how the algorithm translates gender-neutral terms like “doctor” into “he” and “nurse” into “she.”

These biases reflect our own, and it’s not just a data problem. To truly engineer objective AI systems, ones stripped of our society’s biases, we need to ask who is developing these systems, and consult those who will be impacted by the products. In addition to gender, racial bias is also rampant. For example, one recent report found that a supposedly objective crime-predicting system was trained on falsified data, resulting in outputs that further perpetuate corrupt police practices. Another study from Google just this month found that their hate speech detector more often labeled innocuous tweets from African-Americans as “obscene” compared to tweets from people of other ethnicities.

We often think of building AI as purely an engineering job, the panelists agreed. But similar to gene drives, germ-line genome editing, and other transformative—but dangerous—tools, AI needs to grow under the consultation of policymakers and other stakeholders. It pays to start young: educating newer generations on AI biases will mold malleable minds early, alerting them to the problem of bias and potentially mitigating risks.

As panelist Tess Posner from AI4ALL said, AI is rocket fuel for ambition. If young minds set out using the tools of AI to tackle their chosen problems, while fully aware of its inherent weaknesses, we can begin to build an AI-embedded future that is widely accessible and inclusive.

The bottom line: people who will be impacted by AI need to be in the room at the conception of an AI solution. People will be displaced by the new technology, and ethical AI has to consider how to mitigate human suffering during the transition. Just because AI looks like “magic fairy dust doesn’t mean that you’re home free,” the panelists said. You, the sentient human, bear the burden of being responsible for how you decide to approach the technology.

The time for AI is now. Let’s make it ethical.

Image Credit: GrAI / Shutterstock.com Continue reading

Posted in Human Robots

#435520 These Are the Meta-Trends Shaping the ...

Life is pretty different now than it was 20 years ago, or even 10 years ago. It’s sort of exciting, and sort of scary. And hold onto your hat, because it’s going to keep changing—even faster than it already has been.

The good news is, maybe there won’t be too many big surprises, because the future will be shaped by trends that have already been set in motion. According to Singularity University co-founder and XPRIZE founder Peter Diamandis, a lot of these trends are unstoppable—but they’re also pretty predictable.

At SU’s Global Summit, taking place this week in San Francisco, Diamandis outlined some of the meta-trends he believes are key to how we’ll live our lives and do business in the (not too distant) future.

Increasing Global Abundance
Resources are becoming more abundant all over the world, and fewer people are seeing their lives limited by scarcity. “It’s hard for us to realize this as we see crisis news, but what people have access to is more abundant than ever before,” Diamandis said. Products and services are becoming cheaper and thus available to more people, and having more resources then enables people to create more, thus producing even more resources—and so on.

Need evidence? The proportion of the world’s population living in extreme poverty is currently lower than it’s ever been. The average human life expectancy is longer than it’s ever been. The costs of day-to-day needs like food, energy, transportation, and communications are on a downward trend.

Take energy. In most of the world, though its costs are decreasing, it’s still a fairly precious commodity; we turn off our lights and our air conditioners when we don’t need them (ideally, both to save money and to avoid wastefulness). But the cost of solar energy has plummeted, and the storage capacity of batteries is improving, and solar technology is steadily getting more efficient. Bids for new solar power plants in the past few years have broken each other’s records for lowest cost per kilowatt hour.

“We’re not far from a penny per kilowatt hour for energy from the sun,” Diamandis said. “And if you’ve got energy, you’ve got water.” Desalination, for one, will be much more widely feasible once the cost of the energy needed for it drops.

Knowledge is perhaps the most crucial resource that’s going from scarce to abundant. All the world’s knowledge is now at the fingertips of anyone who has a mobile phone and an internet connection—and the number of people connected is only going to grow. “Everyone is being connected at gigabit connection speeds, and this will be transformative,” Diamandis said. “We’re heading towards a world where anyone can know anything at any time.”

Increasing Capital Abundance
It’s not just goods, services, and knowledge that are becoming more plentiful. Money is, too—particularly money for business. “There’s more and more capital available to invest in companies,” Diamandis said. As a result, more people are getting the chance to bring their world-changing ideas to life.

Venture capital investments reached a new record of $130 billion in 2018, up from $84 billion in 2017—and that’s just in the US. Globally, VC funding grew 21 percent from 2017 to a total of $207 billion in 2018.

Through crowdfunding, any person in any part of the world can present their idea and ask for funding. That funding can come in the form of a loan, an equity investment, a reward, or an advanced purchase of the proposed product or service. “Crowdfunding means it doesn’t matter where you live, if you have a great idea you can get it funded by people from all over the world,” Diamandis said.

All this is making a difference; the number of unicorns—privately-held startups valued at over $1 billion—currently stands at an astounding 360.

One of the reasons why the world is getting better, Diamandis believes, is because entrepreneurs are trying more crazy ideas—not ideas that are reasonable or predictable or linear, but ideas that seem absurd at first, then eventually end up changing the world.

Everyone and Everything, Connected
As already noted, knowledge is becoming abundant thanks to the proliferation of mobile phones and wireless internet; everyone’s getting connected. In the next decade or sooner, connectivity will reach every person in the world. 5G is being tested and offered for the first time this year, and companies like Google, SpaceX, OneWeb, and Amazon are racing to develop global satellite internet constellations, whether by launching 12,000 satellites, as SpaceX’s Starlink is doing, or by floating giant balloons into the stratosphere like Google’s Project Loon.

“We’re about to reach a period of time in the next four to six years where we’re going from half the world’s people being connected to the whole world being connected,” Diamandis said. “What happens when 4.2 billion new minds come online? They’re all going to want to create, discover, consume, and invent.”

And it doesn’t stop at connecting people. Things are becoming more connected too. “By 2020 there will be over 20 billion connected devices and more than one trillion sensors,” Diamandis said. By 2030, those projections go up to 500 billion and 100 trillion. Think about it: there’s home devices like refrigerators, TVs, dishwashers, digital assistants, and even toasters. There’s city infrastructure, from stoplights to cameras to public transportation like buses or bike sharing. It’s all getting smart and connected.

Soon we’ll be adding autonomous cars to the mix, and an unimaginable glut of data to go with them. Every turn, every stop, every acceleration will be a data point. Some cars already collect over 25 gigabytes of data per hour, Diamandis said, and car data is projected to generate $750 billion of revenue by 2030.

“You’re going to start asking questions that were never askable before, because the data is now there to be mined,” he said.

Increasing Human Intelligence
Indeed, we’ll have data on everything we could possibly want data on. We’ll also soon have what Diamandis calls just-in-time education, where 5G combined with artificial intelligence and augmented reality will allow you to learn something in the moment you need it. “It’s not going and studying, it’s where your AR glasses show you how to do an emergency surgery, or fix something, or program something,” he said.

We’re also at the beginning of massive investments in research working towards connecting our brains to the cloud. “Right now, everything we think, feel, hear, or learn is confined in our synaptic connections,” Diamandis said. What will it look like when that’s no longer the case? Companies like Kernel, Neuralink, Open Water, Facebook, Google, and IBM are all investing billions of dollars into brain-machine interface research.

Increasing Human Longevity
One of the most important problems we’ll use our newfound intelligence to solve is that of our own health and mortality, making 100 years old the new 60—then eventually, 120 or 150.

“Our bodies were never evolved to live past age 30,” Diamandis said. “You’d go into puberty at age 13 and have a baby, and by the time you were 26 your baby was having a baby.”

Seeing how drastically our lifespans have changed over time makes you wonder what aging even is; is it natural, or is it a disease? Many companies are treating it as one, and using technologies like senolytics, CRISPR, and stem cell therapy to try to cure it. Scaffolds of human organs can now be 3D printed then populated with the recipient’s own stem cells so that their bodies won’t reject the transplant. Companies are testing small-molecule pharmaceuticals that can stop various forms of cancer.

“We don’t truly know what’s going on inside our bodies—but we can,” Diamandis said. “We’re going to be able to track our bodies and find disease at stage zero.”

Chins Up
The world is far from perfect—that’s not hard to see. What’s less obvious but just as true is that we’re living in an amazing time. More people are coming together, and they have more access to information, and that information moves faster, than ever before.

“I don’t think any of us understand how fast the world is changing,” Diamandis said. “Most people are fearful about the future. But we should be excited about the tools we now have to solve the world’s problems.”

Image Credit: spainter_vfx / Shutterstock.com Continue reading

Posted in Human Robots

#435436 Undeclared Wars in Cyberspace Are ...

The US is at war. That’s probably not exactly news, as the country has been engaged in one type of conflict or another for most of its history. The last time we officially declared war was after Japan bombed Pearl Harbor in December 1941.

Our biggest undeclared war today is not being fought by drones in the mountains of Afghanistan or even through the less-lethal barrage of threats over the nuclear programs in North Korea and Iran. In this particular war, it is the US that is under attack and on the defensive.

This is cyberwarfare.

The definition of what constitutes a cyber attack is a broad one, according to Greg White, executive director of the Center for Infrastructure Assurance and Security (CIAS) at The University of Texas at San Antonio (UTSA).

At the level of nation-state attacks, cyberwarfare could involve “attacking systems during peacetime—such as our power grid or election systems—or it could be during war time in which case the attacks may be designed to cause destruction, damage, deception, or death,” he told Singularity Hub.

For the US, the Pearl Harbor of cyberwarfare occurred during 2016 with the Russian interference in the presidential election. However, according to White, an Air Force veteran who has been involved in computer and network security since 1986, the history of cyber war can be traced back much further, to at least the first Gulf War of the early 1990s.

“We started experimenting with cyber attacks during the first Gulf War, so this has been going on a long time,” he said. “Espionage was the prime reason before that. After the war, the possibility of expanding the types of targets utilized expanded somewhat. What is really interesting is the use of social media and things like websites for [psychological operation] purposes during a conflict.”

The 2008 conflict between Russia and the Republic of Georgia is often cited as a cyberwarfare case study due to the large scale and overt nature of the cyber attacks. Russian hackers managed to bring down more than 50 news, government, and financial websites through denial-of-service attacks. In addition, about 35 percent of Georgia’s internet networks suffered decreased functionality during the attacks, coinciding with the Russian invasion of South Ossetia.

The cyberwar also offers lessons for today on Russia’s approach to cyberspace as a tool for “holistic psychological manipulation and information warfare,” according to a 2018 report called Understanding Cyberwarfare from the Modern War Institute at West Point.

US Fights Back
News in recent years has highlighted how Russian hackers have attacked various US government entities and critical infrastructure such as energy and manufacturing. In particular, a shadowy group known as Unit 26165 within the country’s military intelligence directorate is believed to be behind the 2016 US election interference campaign.

However, the US hasn’t been standing idly by. Since at least 2012, the US has put reconnaissance probes into the control systems of the Russian electric grid, The New York Times reported. More recently, we learned that the US military has gone on the offensive, putting “crippling malware” inside the Russian power grid as the U.S. Cyber Command flexes its online muscles thanks to new authority granted to it last year.

“Access to the power grid that is obtained now could be used to shut something important down in the future when we are in a war,” White noted. “Espionage is part of the whole program. It is important to remember that cyber has just provided a new domain in which to conduct the types of activities we have been doing in the real world for years.”

The US is also beginning to pour more money into cybersecurity. The 2020 fiscal budget calls for spending $17.4 billion throughout the government on cyber-related activities, with the Department of Defense (DoD) alone earmarked for $9.6 billion.

Despite the growing emphasis on cybersecurity in the US and around the world, the demand for skilled security professionals is well outpacing the supply, with a projected shortfall of nearly three million open or unfilled positions according to the non-profit IT security organization (ISC)².

UTSA is rare among US educational institutions in that security courses and research are being conducted across three different colleges, according to White. About 10 percent of the school’s 30,000-plus students are enrolled in a cyber-related program, he added, and UTSA is one of only 21 schools that has received the Cyber Operations Center of Excellence designation from the National Security Agency.

“This track in the computer science program is specifically designed to prepare students for the type of jobs they might be involved in if they went to work for the DoD,” White said.

However, White is extremely doubtful there will ever be enough cyber security professionals to meet demand. “I’ve been preaching that we’ve got to worry about cybersecurity in the workforce, not just the cybersecurity workforce, not just cybersecurity professionals. Everybody has a responsibility for cybersecurity.”

Artificial Intelligence in Cybersecurity
Indeed, humans are often seen as the weak link in cybersecurity. That point was driven home at a cybersecurity roundtable discussion during this year’s Brainstorm Tech conference in Aspen, Colorado.

Participant Dorian Daley, general counsel at Oracle, said insider threats are at the top of the list when it comes to cybersecurity. “Sadly, I think some of the biggest challenges are people, and I mean that in a number of ways. A lot of the breaches really come from insiders. So the more that you can automate things and you can eliminate human malicious conduct, the better.”

White noted that automation is already the norm in cybersecurity. “Humans can’t react as fast as systems can launch attacks, so we need to rely on automated defenses as well,” he said. “This doesn’t mean that humans are not in the loop, but much of what is done these days is ‘scripted’.”

The use of artificial intelligence, machine learning, and other advanced automation techniques have been part of the cybersecurity conversation for quite some time, according to White, such as pattern analysis to look for specific behaviors that might indicate an attack is underway.

“What we are seeing quite a bit of today falls under the heading of big data and data analytics,” he explained.

But there are signs that AI is going off-script when it comes to cyber attacks. In the hands of threat groups, AI applications could lead to an increase in the number of cyberattacks, wrote Michelle Cantos, a strategic intelligence analyst at cybersecurity firm FireEye.

“Current AI technology used by businesses to analyze consumer behavior and find new customer bases can be appropriated to help attackers find better targets,” she said. “Adversaries can use AI to analyze datasets and generate recommendations for high-value targets they think the adversary should hit.”

In fact, security researchers have already demonstrated how a machine learning system could be used for malicious purposes. The Social Network Automated Phishing with Reconnaissance system, or SNAP_R, generated more than four times as many spear-phishing tweets on Twitter than a human—and was just as successful at targeting victims in order to steal sensitive information.

Cyber war is upon us. And like the current war on terrorism, there are many battlefields from which the enemy can attack and then disappear. While total victory is highly unlikely in the traditional sense, innovations through AI and other technologies can help keep the lights on against the next cyber attack.

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